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It is extremely
important that we
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monitor CO2, because it is
an important greenhouse gas.
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And satellite data
inform us on how
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to model and represent the CO2.
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This image is actually
based on a model simulation,
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on a model forecast of the
CO2 cycle for September, 2014.
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And you can see
the amazing detail
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of the cycle of respiration
and photosynthesis.
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The green values are
below the ground,
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and that's the activity of
the plants in late summer
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producing, actually removing
CO2 from the atmosphere
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and producing oxygen.
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So you see like it's
below the ground.
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Whereas the red
spots that you see
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are associated with
production of the CO2,
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and those are
associated to wildfires
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or anthropogenic activity.
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And just the cycle of vegetation
and when it's the dry season.
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Likewise, we have a
simulation here of a dust
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storm from the satellite data.
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And you can see that the
dust produced in the desert
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by uplifting, by the wind,
it's transported all of the way
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across Europe.
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And it affects air quality
in most of southern Europe.
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This image is based
on satellite data that
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are incorporated in the model.
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They provide initial condition
for their model simulation,
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for the prediction.
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And then images like
this can be realised.
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And this is actually a
prediction into the future,
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five days ahead.
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A recent mission that
was launched this July
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is the orbiting
Carbon Observatory.
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And that's going
to allow scientists
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to observe the amount of
carbon that's currently
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in the atmosphere with
hundreds of thousands
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of measurements made every
day, and at a global scale.
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So we can track
where those emissions
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came from by running atmospheric
transfer models in reverse.
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Atmospheric transfer models
are what tell you, for example,
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if I emitted carbon right here,
where would it be in two hours?
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Where would be in two days?
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Where would be in two weeks?
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Et cetera.
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So when we're able
to see where carbon
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is in the atmosphere from space,
we run those models in reverse
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and we find out
where it originated.
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And that's going to
help us when we're
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trying to estimate
how much carbon was
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emitted by a certain country.
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So policy considerations
require us
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to have spatially explicit
estimates of carbon emissions.
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And the orbiting
Carbon Observatory
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will allow us to do that.
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Another variable that
we constantly monitor
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is fire emissions, and this is
essential for our prediction
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system.
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We can see here images of a
fire raging in South Africa
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and in Spain and
Portugal, and these images
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are amazingly detailed.
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They show the
location of the fires,
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and also the smoke coming
out of these fires.
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This type of data
can really help
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us have a successful prediction
of this type of event.
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A great example of that was from
2013, when raging fires were
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happening in Canada.
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It's normal that
you have wildfires.
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However, the type of circulation
that year was so strong,
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was so intense, that
the smoke from the fires
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made all the way across
the Atlantic into Europe
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and were actually observed by
ground based sensing lighters,
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sensinometors.
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You can see a satellite
image of the smoke,
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and this took-- along with
other data-- for example,
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data the MODIS satellite, from
the Yazi satellite, the CO
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product, and the data
from Mopit as well CO,
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went into the
analysis and produced
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exactly this type of forecast.
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You can really see the
details of the plume being
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affected by the winds all the
way from Canada to Europe.
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And although in
this case the smoke
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stayed at elevated levels
between two and six
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kilometres-- so it was
not really affecting
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air quality at the
surface, people
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may have wondered about the
hazy quality of the skies,
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and they may have
actually been surprised
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had they know that the smoke was
coming all the way from Canada.
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And the forecast is
based on this product
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that I mentioned earlier,
the fire emissions that
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are based on the satellite
data that we receive daily.
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In that case, air
quality was not
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affected, because
the layer of smoke
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stayed between two
and six kilometres.
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But it's interesting
and important
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to monitor these
type of situations,
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because in a changing climate,
they may be more recurring
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and may end up affecting,
perhaps, air quality.
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